The subject matter disclosed herein generally relates to communications involving wireless devices and more particularly to methods and systems for managing differentiated wireless device traffic such as machine to machine (M2M) traffic to manage network performance.
The rapid development of telecommunications technologies has allowed providers of a wide range of services to manage and control devices remotely. M2M devices communicate with other devices and/or systems of similar capabilities. M2M devices have applications in a variety of service areas including security, tracking and tracing, payment, health, remote maintenance and control, metering, and consumer devices. Examples of M2M type devices include temperature sensors, water meters, electric meters, gas meters, automotive navigation aids, emergency notification, digital billboards, or the like. Typically, an M2M device acquires information (e.g., temperature, utility usage, documents, etc.) and provides the information to another device via a network. Because of the large number of potential applications, M2M is expanding at an unprecedented pace, and it is forecasted that through exponential growth there will be 50 billion devices by 2020. Due to the increasing number of M2M devices entering the marketplace and the resulting traffic, it is likely that network congestion may occur.
A typical cellular network includes a radio access network and a core network. The key core network components are a database of device locations and security keys and the “front end workers” that are the computers/servers in front of it to allow many transactions per second. The core network is designed for the rapid response needed for making synchronous voice calls. Much of the cost of network elements like the Home Location Register/Home Subscriber Service (HLR/HSS) is driven by the low latency required to connect to the network and the network locating the other party. This all happens within milliseconds. The lower the latency needs, the more front end worker resources that must be applied.
Currently all M2M traffic is treated equally, which results in network congestion when massive numbers of machines are attempting to communicate with each other simultaneously. Consequently, today there is a single “quality” level at the core network. However, not all M2M communications require the same Quality of Service (QoS) as synchronous voice communications, in that M2M communications may have a higher latency tolerance than synchronous voice communications.
Services like voice calls require high QoS via low latency. Video has high data throughput requirements. These needs have driven the development of network air interface bearers and the ability to assign the resources to ensure service experiences. The maturity of QoS is around allocation of the scarce radio access network resources of which are primarily spectrum. With M2M traffic there is often a high tolerance for latency to transmit very small amounts of data. However, the macro cellular network is dimensioned to be able to support high QoS services like voice and video. Even though M2M devices may use very little throughput meaning they do not consume much of the scarcest resource of spectrum, overall costs to operate an M2M network are high, partly driven by the bottleneck (and cost) moving into the core network. Therefore, there is a need for methods and systems to manage M2M traffic in a way that reduces network congestion. There is a need for a method and system to manage M2M traffic based on the QoS requirements and latency needs of M2M devices.